Share This Article:

Detection ischemic episodes from electrocardiogram signal using wavelet transform

Abstract Full-Text HTML Download Download as PDF (Size:313KB) PP. 239-244
DOI: 10.4236/jbise.2009.24037    5,379 Downloads   10,004 Views   Citations


In this paper, we propose an algorithm for de-tection of myocardial ischemic episodes from electrocardiogram (ECG) signal using the wavelet transform technique. The algorithm was tested on data from the European ST-T change database. Results show that this algorithm is effective for distinguishing normal ECGs from ischemic. We developed a method that uses wavelets for extracting ECG patterns that are characteristic for myocardial ischemia.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Karimi Moridani, M. and Pouladian, M. (2009) Detection ischemic episodes from electrocardiogram signal using wavelet transform. Journal of Biomedical Science and Engineering, 2, 239-244. doi: 10.4236/jbise.2009.24037.


[1] N. Sivannarayana, D. C. Reddy, (1999) Biorthogonal wavelet transforms for ECG parameters estimation, 167-174.
[2] N. Milosavljevic and A. Petrovic, (2006) ST segment change detection by means of wavelets, 137-140.
[3] P. Ranjith, P. C. Baby, and P. Joseph, (2003) ECG analy-sis using wavelet transform: application to myocardial ischemia detection, 44-47.
[4] “European ST-T change database,” www.
[5] N. Magaveras, T. Stamkopoulos, C. Pappas, and M. G. Strintzis, (1998) An adaptive backpropagation neural network for real-time ischemia episodes detection: De-velopment and performance analysis using the European ST-T database, IEEE Trans Biomed Eng, 45, 805-13.
[6] M. Vetterly and J. Kovacevic, (1995) Wavelet and sub-band coding, First Edition, Upper Saddle River, NJ: Prentice Hall.
[7] M. R. Raghuveer and S. Bopardikar, (1996) Wavelet transforms: Introduction to theory and applications, Sec-ond Edition, Boston, MA: Addison Wesley.
[8] (1996) Special issue on wavelets, Proc IEEE, 84(4).
[9] S. Mallat and S. Zhong, (1992) Characterization of sig-nals from multiscale edges, IEEE Trans PAMI, 14(7).
[10] C. Li, C. Zheng, and C. Tai, (1995) Detection of ECG characteristic points using wavelet transform, IEEE Trans Biomed Eng, 42(1), 8-21.
[11] D. P. Golden, R. A. Wolthuis, and G. W. Hoffler, (1973) A spectral analysis of the normal resting electrocardiogram, IEEE Trans Biomed Eng, 20(5), 366-72.
[12] S. Mallat, (1991) Zero crossing of a wavelet transform, IEEE Trans Inf Theory, 37(4).
[13] P. F. Cohn, (1993) Silent myocardial ischemia and infarc-tion, 8–18, NewYork: Marcel Dekker, 87-97.
[14] F. Jager, G. B. Moody, and R. G. Mark, (1998) Detection of transient ST segment episodes during ambulatory ECG monitoring, Comput Biomed Res, 31(5), 305-22.
[15] J. Garcia, L Sornmo, S. Olmos, P. Laguna, (2000) Auto-matic detection of ST–T complex changes on the ECG using filtered RMS difference series: Application to am-bulatory ischemia monitoring, IEEE Trans Biomed Eng; 47(9), 1195-201.
[16] F. Jager, G. B. Moody, A. Taddei, R. G. Mark, (1991) Per-formance measures for algorithms to detect transient ischemic ST segment changes. Computers in Cardiology, Los Alamitos, CA: IEEE Computer Society Press, 372-96.

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.